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[马尾松林叶片总叶绿素与高光谱特征关系研究]

[Study on relationships between total chlorophyll with hyperspectral features for leaves of Pinus massoniana forest].

作者信息

Du Hua-Qiang, Ge Hong-Li, Fan Wen-Yi, Jin Wei, Zhou Yu-Feng, Li Jin

机构信息

School of Environmental Sciences and Technology, Zhejiang Forestry College, Hangzhou 311300, China.

出版信息

Guang Pu Xue Yu Guang Pu Fen Xi. 2009 Nov;29(11):3033-7.

PMID:20101980
Abstract

In the present study, the authors built the relationships between the total chlorophyll and hyperspectral features of P. massoniana. The research results showed that (1) chlorophyll content has a good linear relationship with spectral reflectance around 527, 703, 1 364 and 1 640 nm, and this result is helpful for us to select some important bands when monitoring P. massoniana by remote sensing image; (2) all of the nine kinds of spectral feature parameters including red edge position, mean reflectance of red edge, mean reflectance around red edge position, red edge slope, red edge area, absorption depth of red band, green peak height, red edge normalized difference vegetation index and red edge vegetation stress index, have exponential function relationship (r = 0.5-0.7) with the total chlorophyll; (3) the total chlorophyll content can be predicted by multivariate model by the nine spectral feature parameters, and partial least-squares regression model have higher prediction accuracy than the traditional multivariate linear model. The model's root mean square (RMS) is 0.008 8, and mean absolute percentage error is 0.761 7%. During the growth of vegetation, biochemical parameters such as chlorophyll have vital function, for example, it can indicate the health status or pathological feature. So, the models mentioned just above will help us understand the ecological process of P. massoniana forest and provide valuable reference for monitoring P. massoniana and pine wood nematode disease by remote sensing technique.

摘要

在本研究中,作者建立了马尾松总叶绿素与高光谱特征之间的关系。研究结果表明:(1)叶绿素含量与527、703、1364和1640nm附近的光谱反射率具有良好的线性关系,这一结果有助于我们在利用遥感影像监测马尾松时选择一些重要波段;(2)包括红边位置、红边平均反射率、红边位置附近平均反射率、红边斜率、红边面积、红波段吸收深度、绿峰高度、红边归一化差异植被指数和红边植被胁迫指数在内的九种光谱特征参数,均与总叶绿素呈指数函数关系(r = 0.5 - 0.7);(3)利用这九种光谱特征参数通过多元模型可预测总叶绿素含量,偏最小二乘回归模型的预测精度高于传统多元线性模型。该模型的均方根(RMS)为0.008 8,平均绝对百分比误差为0.761 7%。在植被生长过程中,叶绿素等生化参数具有重要作用,例如,它可以指示健康状况或病理特征。因此,上述模型将有助于我们了解马尾松林的生态过程,并为利用遥感技术监测马尾松和松材线虫病提供有价值的参考。

相似文献

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[Study on relationships between total chlorophyll with hyperspectral features for leaves of Pinus massoniana forest].[马尾松林叶片总叶绿素与高光谱特征关系研究]
Guang Pu Xue Yu Guang Pu Fen Xi. 2009 Nov;29(11):3033-7.
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引用本文的文献

1
Research Progress on the Early Monitoring of Pine Wilt Disease Using Hyperspectral Techniques.基于高光谱技术的松材线虫病早期监测研究进展。
Sensors (Basel). 2020 Jul 3;20(13):3729. doi: 10.3390/s20133729.